Measuring Efficiency of Total Productive Maintenance (TPM) with Newly Developed Performance Measures using Fuzzy Data Envelopment Analysis

Transcription

1 Proceeding of the World Congre on Engineering 216 Vol I, June 29 - July 1, 216, ondon,.k. Meauring Efficiency of Total Productive Maintenance (TPM with Newly Develoed Perforance Meaure uing Fuzzy Data Enveloent Analyi E. Turanoglu Bekar, and C. Kahraan Abtract Total Productive Maintenance (TPM ha been widely acceted a a trategic tool for ucceeding anufacturing erforance and alo it ha been effectively ileented in any organization. The evaluation of TPM efficiency can ake a great contribution to coanie in advancing their oeration acro a variety of dienion. Thi tudy ai to rooe a new fraework for evaluation TPM erforance. Prooed TPM effectivene yte can be divided into three tage: (i the deign of the new erforance eaure, (ii the evaluation of the new erforance eaure, and (iii the ue of the new erforance eaure to evaluate TPM effectivene. Finally, rooed fuzzy DEA ethod i ued to evaluate TPM erforance with newly develoed erforance eaure uing real anufacturing cae. In thi tudy, the fuzzy utility degree achieved fro fuzzy COPRAS are integrated with fuzzy DEA in order to deterine efficient and inefficient TPM erforance. Index Ter Fuzzy COPRAS, Fuzzy Data Enveloent Analyi, Total Productive Maintenance (TPM, erforance evaluation, erforance eaure in TPM T I. INTRODCTION PM ileentation and alying i a yteatic activity throughout the organization. It require a ignificant change culturally and will be a lifetyle. Thu, to eaure TPM alication effectivene, it hould be needed a yteatic rogra baed on different factor having iact on TPM affecting the whole organization. When it coe to erforance evaluation in TPM, overall equient effectivene (OEE ha coonly been ued a a erforance eaure ince TPM ai to axiize equient effectivene [1]-[2]. Although OEE ha been conidered a a tandard eaure for equient erforance [3], what it cature i only effectivene of TPM, not efficiency. In ot coanie, when evaluating the erforance of TPM, only OEE i conidered. However, the erforance evaluation of TPM hould include an obective and corehenive ethod baed on ultile inut and outut. E. Turanoglu Bekar i with the Izir niverity, Izir, 3535 TRKEY (correonding author: ; fax: ; e-ail: ebru.turanoglu@ izir.edu.tr. C. Kahraan i with Itanbul Technical niverity, Itanbul, TRKEY. (e-ail: kahraanc@itu.edu.tr. Since the evaluation contain ultile inut and outut, it can be conidered of a a ulti-criteria deciion aking roble. In the literature, a few tudie have been ade referred to the efficiency eaureent in TPM ileentation. In thee tudie, Wang [4] and Jeon et al. [5] were ued DEA to eaure the efficiency of TPM ileentation. Alo a nuber of tudie have been conducted to identify iortant factor in TPM [6]-[11]. Therefore, the otivation for thi reearch i develoed new erforance eaure in TPM and evaluated thee erforance eaure under fuzzy environent and then claified into TPM inut and outut. Finally they are erfored to eaure TPM efficiency uing fuzzy DEA. II. METHOD In thi tudy, rooed TPM effectivene yte can be divided into three tage: (i the deign of the new erforance eaure, (ii the evaluation of the new erforance eaure, and (iii the ue of the new erforance eaure to evaluate TPM effectivene. The current reult indicate that there hould be ore ue of TPM a a erforance develoent roce. It iroveent ut be eaured, both ubectively and quantitatively a uoed in the literature. So there are a large nuber of tangible and intangible factor, which often are in conflict with each other, that hould be conidered in develoent of new erforance eaure in TPM. In thi tudy, the fuzzy utility degree achieved fro fuzzy COPRAS were integrated with fuzzy DEA in order to deterine efficient and inefficient TPM erforance. The flow diagra of the integrated fuzzy COPRAS-fuzzy DEA ethod i hown in Figure 1. A. iterature Review on Fuzzy DEA Method In thi tudy, an integrated fuzzy COPRAS- fuzzy DEA ethod are conducted o we exaine oe article that oin different deciion aking technique with fuzzy DEA and irove hybrid ethod. However, in the literature there are few tudie that ue fuzzy DEA in ultiattribute deciion aking roble. In one of the ot referenced aer Ertay et al. [12] integrate fuzzy DEA with analytic hierarchy roce (AHP for deigning of facility layout which can deal with both qualitative and quantitative data.

2 Proceeding of the World Congre on Engineering 216 Vol I, June 29 - July 1, 216, ondon,.k. Fig. 1. The flow diagra of the integrated fuzzy COPRAS-fuzzy DEA ethod. In a different aer, iu [13] irove a fuzzy DEA/AR (aurance region ethod which can ae the erforance of flexible anufacturing yte otion where the inut and outut data can be fuzzy a well a cri value. Wu [14] ugget a cobined technique uing DEA and fuzzy reference relation to rank deciion alternative. Kuo et al. [15] integrate both fuzzy AHP and fuzzy DEA ethod for aiting organization to elect roer ulier. Zhou et al. [16] offered generalized fuzzy DEA odel with GFDEA/AR to evaluate the erforance of anufacturing enterrie uing different cae. Awathi et al. [17] reent a ultite aroach baed on fuzzy DEA aroach for ulier quality evaluation. According to literature review and the bet knowledge of the author, thi i the firt tudy that integrate fuzzy COPRAS-fuzzy DEA ethod to evaluate erforance efficiency of TPM with newly develoed erforance eaure. B. Fuzzy DEA Methodology We conider that there are n DM and each DM ue differing aount of different fuzzy inut to roduce different fuzzy outut. Secifically, DM ue aount x i of inut to roduce aount odel forulation, x i and y r of outut. In the yr denote, reectively, the inut and outut value for the DM. In order to exlain the fuzzy BBC (variable return-to-cale a introduced in Banker et al. [18] odel, Kao and iu [19] rooed a air of two-level atheatical odel to calculate the lower bound ( w and uer bound ( w of the fuzzy efficiency core for a ecific α-level a follow: (w ax Xixi Xi Yr yr Yr r,, i w axur yr u r1. t. vi xi 1, i1 ur yr vi xi u,, r1 i1 ur, vi, r, i. where [(X i,(x i ] and [(Y r,(y r ] are α-level for of the fuzzy inut and the fuzzy outut reectively. Thi two-level atheatical odel can be clarified to the conventional one-level odel a follow: ur r r1 (w ax (Y. t. u (Y v (X u, r r i i r1 i1 i1 u r r i i r1 i1 u (Y v (X u,,, v (X 1, u, v,. i i r i r,i ur r r1 (w ax (Y. t. u (Y v (X u, r r i i r1 i1 i1 u (Y v (X u,,, v (X 1, u, v,. i i r i r,i u r r i i r1 i1 Next, a eberhi function i built by olving the lower and uer bound [(w,(w ] of the α-level for each DM uing odel (1 and (2. III. PERFORMANCE EVAATION OF TPM THROGH FZZY DEA: A REA MANFACTRING CASE A. Definition of Deciion Making nit (DM Thi tudy i conidered to be ileented in a coany oerating in the autootive indutry in Aegean Free Zone ince Direct and 13 indirect eloyee work in the coany. Along with core oerating deartent, there are uort function including TPM deartent. In TPM deartent, there are 1 lead engineer and 4 uervior and 28 aintenance technician. The overall TPM activitie of thi coany are anaged by the TPM-office.. In thi tudy, we ue the rooed fuzzy DEA odel to evaluate the erforance efficiency of TPM for four roduction line (DM uch a Rail Machining (DM1, Rail Aebly and HPV (DM2, NHB Beginning of ine (BO (DM3 and NHB End of ine (EO (DM4. (1 (2 (3

3 Proceeding of the World Congre on Engineering 216 Vol I, June 29 - July 1, 216, ondon,.k. B. Definition of Inut and Outut The newly develoed erforance eaure that are to be iniized are viewed a inut, wherea the one to be axiized are conidered a outut throughout the TPM erforance evaluation tudy. The deciion fraework involve the evaluation of the relative TPM efficiency of four roduction line with reect to even outut and ten inut given a in Table 1. Table 1 alo how the fuzzy weight of inut and outut were deterined by fuzzy COPRAS. The inut Availability of aintenance eronnel, Oerator reliability and Refual of extended hour or overtie are evaluated fro obervation of roduction line uervior and tea leader uing fuzzy linguitic cale uch a very low, low, ediu, high and very high and their eberhi function are hown a in Figure 2. Fig. 2. The Meberhi function of the inut Availability of Maintenance Peronnel, Oerator Reliability and Refual of extended hour or overtie. TABE 1 THE FZZY WEIGHTS OF INPTS AND OTPTS OBTAINED BY FZZY COPRAS Category Outut Fuzzy Weight Mean Tie to (.536,.573, Reair (MTTR.611 NEWY DEVEOPED PERFORMANCE MEASRES Oerational Related Environental, Health & Safety Proble Direct Huan Factor Mean Tie Between Failure (MTBF Nuber of unlanned aintenance (.512,.547,.584 (.554,.593,.634 Reduced eed (.555,.589,.624 Reduced yield (.575,.66,.639 Quality defect (.552,.586,.622 Nuber of afety, health and environent incident Inut Availability of aintenance eronnel Coetence of aintenance eronnel Exerience of oerator in roduction line Oerator reliability Training and continuing education (.474,.526,.582 (.448,.57,.567 Indirect Huan Factor Buine Related Motivational Manageent Work environent Organization roble & labour unret (Eloyee atifaction New idea generated and ileented evel of 5S Eloyee abentee Eloyee turnover rate Refual of extended hour or overtie (.415,.464,.514 (.415,.464,.514 (.415,.464,.514 According to the obective function of DEA, it i eential to convert the outut indicant into fractional nuber a large a oible and the inut indicant a all a oible. C. Data Decrition and Noralization All inut and outut data regarding the four roduction line (DM are defined aroxiate value, cri data or linguitic ter. Then the inut and outut data deterined by cri and aroxiate value and linguitic ter are tranfored triangular fuzzy nuber. Table 2 lit fuzzy value for all inut and outut. In order to refine the roble becaue of the iortant difference in the agnitude of inut and outut, the linear cale tranforation i erfored to the different inut and outut cale into a coarable cale. Therefore, we can get the noralized fuzzy value of inut and outut denoted by R r i,the triangular fuzzy nuber(tfn x i=(a i,b i,c i, B and C are the et of benefit inut and outut and cot inut and outut, reectively, and ai bi c i r,,, B; * * * c c c a a a r,,, C; ci bi a i * ax c ci if B; (6 i in a ai if C; (7 i The noralization ethod noted above i to rotect the roerty that the range of noralized triangular fuzzy nuber belong to [; 1]. D. Integrating Fuzzy COPRAS with Fuzzy DEA Thi tudy integrate both fuzzy COPRAS and fuzzy DEA ethod to evaluate TPM erforance in the coany. A noted earlier, we can ue fuzzy COPRAS to obtain the range of weight for inut and outut. After erforing thee weight into fuzzy DEA odel develoed by Kao and iu (2 whoe atheatical rereentation were given in Eq Firtly we have obtained the α-cut et of inut and outut for the each roduction line (DM given a in Table 3. Then, for the lower and uer bound of each DM we have etablihed atheatical odel in order to analyze the erforance efficiency of TPM. (4 (5

4 MTTR (u 1 (.76, 1.59, 2.42 (.99, 1.24, 1.49 (.49, 1.8, 3.11 (.68, 1.11, 1.79 MTBF (u 2 (85.67, 12.99, (55.94, 78.66, (15.21, , (27.52, 63.43, Nuber of nlanned Maintenance (u 3 (59.31, 76.19, 93.7 (8.45, 14.51, (137.69, , (41.63, , Minute (Mean-Standard Deviation Minute (Mean-Standard Deviation Nuber (Mean-Standard Deviation Proceeding of the World Congre on Engineering 216 Vol I, June 29 - July 1, 216, ondon,.k. TABE 2 FZZY VAES OF A INPTS AND OTPTS FOR FOR PRODCTION INES PRODCTION INES (DMS NITS INPTS DM1 DM2 DM3 DM4 Availability of aintenance eronnel (v 1 (3, 5, 7 (1, 3, 5 (3,5, 7 (5, 7, 9 inguitic Scale Coetence of aintenance eronnel (v 2 (8, 82, 84 (83, 85, 87 (65, 67, 69 (76, 78, 8 Exerience of oerator in roduction line (v 3 (7., 7.2, 7.4 (6.2, 6.4, 6.6 (4.3, 4.5, 4.7 (3.8, 4., 4.2 Year Point Scoring Syte ( To 1 Oerator reliability (v 4 (5, 7, 9 (1, 3, 5 (3, 5, 7 (5, 7, 9 inguitic Scale Training and continuing education (v 5 (1, 14, 18 (13, 17, 21 (11, 15, 19 (12, 16, 2 Hour er Year New idea generated and ileented (v 6 (16, 18, 2 (8, 1, 12 (4, 6, 8 (6, 8, 1 Avg. Point Gained/Eloyee evel of 5S (v 7 (3.21, 3.71, 4.21 (3.33, 3.83, 4.33 (3.5, 4., 4.5 (3.33, 3.83, 4.33 Point Scoring Syte (1 To 5 Eloyee abentee (v 8 (1.9, 1.39, 1.69 (1.5, 1.8, 2.1 (1.79, 2.9, 2.39 (1.7, 1.37, 1.67 % Eloyee turn-over rate (v 9 (.1,.3,.5 (.4,.6,.8 (1., 1.2, 1.4 (.5,.7,.9 % Refual of extended hour or overtie (v 1 (1, 3, 5 (3, 5, 7 (5, 7, 9 (3, 5, 7 inguitic Scale OTPTS Nuber of afety, health and environent incident (u 4 (.75,.77,.79 (1.78, 1.8, 1.82 (1.1, 1.3, 1.5 (1.53, 1.55, 1.57 Incident er Man Hour Reduced eed (u 5 (2413, 2473, 2533 (1696, 1756, 1816 (21, 27, 213 (1774, 1834, 1894 Minute Reduced yield (u 6 (94.5, 99., (88.35, 93., (92.15, 97., (9.25, 95., % Quality defect (u 7 (.95, 1., 1.5 (6.65, 7., 7.35 (2.85, 3., 3.15 (4.75, 5., 5.25 %

5 Outut Proceeding of the World Congre on Engineering 216 Vol I, June 29 - July 1, 216, ondon,.k. TABE 3 THE -CT SETS OF INPTS AND OTPTS DM Inut

6 Proceeding of the World Congre on Engineering 216 Vol I, June 29 - July 1, 216, ondon,.k. By olving atheatical odel for the lower and uer bound for each of the DM uing INGO 14. reectively, we get fuzzy efficiencie for every DM. Table 4 lit the fuzzy efficiencie of each DM (roduction line under the α-cut level a,.1,.2,.3,.4,.5,.6,.7,.8,.9 and 1.. TABE 4 THE FZZY EFFICIENCIES ACCORDING TO -CT EVES DM α DM α Table 4 reveal that only DM1 ha the highet TPM erforance value. The other third DM erforance value are all aller than 1. The DM2 ha the lowet TPM erforance value. Fro the lower bound and uer bound of efficiency value, it i oberved that roduction line DM1, DM4 and DM3 together define an efficient frontier and DM4 i the roduction line with the bet erforance followed by roduction line DM1 according to TPM erforance. IV. CONCSION In thi tudy, a new fraework i uggeted to eaure TPM efficiency uing fuzzy DEA. Fuzzy DEA i alied for evaluation of TPM erforance with newly develoed erforance eaure uing real anufacturing cae. Alo fuzzy COPRAS with fuzzy value are reented to decribe the inut and outut weight. Thi ethod i able to adat eaily to all indutrie. A cae tudy on a globally autootive coany indicated that the rooed ethod actually ha the above-entioned advantage. By the reult roduced by the uggeted ethod, thi coany can ake oe reviion for it roduction line in order to achieve ore intereting outcoe. For the future reearch, other fuzzy DEA ethod baed on fuzzy ranking aroach, the oibility aroach and tye-2 fuzzy et will be eloyed to eaure TPM efficiency. Alo it will be added another real anufacturing cae for a coany oerating in a different ector. REFERENCES [1] W.A.J. Schier, An integrated aroach to roce control, International Journal of Production Econoic, vol. 69, , 21. [2] G. Waeyenbergh and. Pintelon, A fraework for aintenance concet develoent, International Journal of Production Econoic, vol. 77, no. 3, , 22. [3] F.T.S. Chan, H.C.W. au, R.W.. I, H.K. Chan and S. Kong, Ileentation of Total Productive Maintenance: a cae tudy, International Journal of Production Econoic, vol. 95, , 25. [4] F-K Wang, Evaluating the Efficiency of Ileenting Total Productive Maintenance, Total Quality Manageent, vol. 17, no. 5, , 26. [5] J. Jeon, C. Ki and H. ee, Meauring efficiency of total roductive aintenance (TPM: a three-tage data enveloent analyi (DEA aroach, Total Quality Manageent & Buine Excellence, vol. 22, no. 8, , 211. [6]. Swanon, inking aintenance trategie to erforance, International Journal of Production Econoic, vol. 7, no. 3, , 21. [7] K.O. Cua, K.E. McKone and R.G. Schroeder, Relationhi between ileentation of TQM, JIT, and TPM and anufacturing erforance, Journal of Oeration Manageent, vol. 19, no. 6, , 21. [8] K.E. McKone, R.G. Schroeder and K.O. Cua, The iact of total roductive aintenance ractice on anufacturing erforance, Journal of Oeration Manageent, vol. 19, no.1, , 21. [9] I.P.S. Ahua and J.S. Khaba, An evaluation of TPM initiative in Indian indutry for enhanced anufacturing erforance, The International Journal of Quality & Reliability Manageent, vol. 25, no. 2, , 28. [1] O. ungberg, Meaureent of overall equient effectivene a a baic for TPM activitie, International Journal of Oeration and Production Manageent, vol. 18, no. 5, , [11] R.K. Shara, D. Kuar and P. Kuar, Manufacturing excellence through TPM ileentation: A ractical analyi, Indutrial Manageent & Data Syte, vol. 16, no. 2, , 26. [12] T. Ertay, D. Ruan and.f. Tuzkaya, Integrating data enveloent analyi and analytic hierarchy for the facility layout deign in anufacturing yte, Inforation Science, vol. 176, , 26. [13] S.T. iu, A fuzzy DEA/AR aroach to the election of flexible anufacturing yte, Couter and Indutrial Engineering, vol. 54, , 28. [14] D.D. Wu, Perforance evaluation: an integrated ethod uing data enveloent analyi and fuzzy reference relation, Euroean Journal of Oeration Reearch, vol. 194, , 25. [15] R.J. Kuo,.Y. ee and T-. Hu, Develoing a ulier election yte through integrating fuzzy AHP and fuzzy DEA: a cae tudy on an auto lighting yte coany in Taiwan, Production Planning & Control, vol. 21, no. 5, , 21. [16] Z. Zhou,. Zhao, S. ui and C. Ma, A generalized fuzzy DEA/AR erforance aeent odel, Matheatical and Couter Modelling, vol. 55, , 212. [17] A. Awathi, K. Nohad and S.S. Chauan, Sulier Perforance Evaluation ing a Hybrid Fuzzy Data Enveloent Analyi Aroach, in Perforance Meaureent with Fuzzy Data Enveloent Analyi. Studie in Fuzzine and Soft Couting, Vol. 39, A. Erouznead and M. Tavana Ed. Berlin Heidelberg: Sringer-Verlag, 214, ch. 14. [18] R.D. Banker, A. Charne and W.W. Cooer, Soe odel for the etiation of technical and cale inefficiencie in Data Enveloent Analyi, Manageent Science, vol. 3, , [19] C. Kao and S.T. iu, Fuzzy efficiency eaure in data enveloent analyi, Fuzzy Set and Syte, vol. 113, no. 3, , 2.